This page explains how the GPXZ dataset is built. To learn more about how to use the gpxz.io API see the API docs.
The GPXZ elevation dataset is a composite dataset made by combining multiple open sources of elevation data.
Our dataset covers the entire globe:
- Ice-surface elevation is given at the poles.
- Bathymetry (depth below sea level) is included in the dataset. Most GPXZ API endpoints have an option to remove bathymetry and return an elevation of 0 for locations at sea.
Coverage and resolution
The GPXZ dataset starts with a base of ocean depth from GEBCO 2023 and land elevation from the 30m Copernicus data source.
On top of those base sources, high-resolution lidar datasets are layered where available.
Here's how the coverage looks around the world.
- While lidar coverage for your country of interest may look patchy, these source datasets usually prioritise areas where people live and which researchers study.
- Resolution is given in metres, and represents horizontal precision. A 30m dataset will be unable to capture topographic features smaller than 30m.
Basemaps thanks to OpenStreetMap.
The GPXZ dataset is made by layering open elevation sources.
- For sources that have a non-bathymetric elevation values over ocean areas (either sea-surface height or dummy values), this is removed.
- Small holes are filled using kriging. (Large holes will be filled during merging).
- Source-specific preprocessing is done to remove known areas of corruption and noise.
2. Land merge
- Land source rasters are merged using the algorithm described in Petrasova et al (2017). A max merge angle of 2° is used.
3. Ocean merge
- The merged land elevation raster is then merged with bathymetry.
- The algorithm used to merge the land data leaves a zone of intermediary-quality inside the edge of the hi-res raster. This would be a problem bathymetry merging as these datasets are often low resolution, and coastal data is important for many end users.
- Instead, an estimated elevation profile is linearly interpolated from the edge of the land data out to a distance of 1km offshore. Next, a distance-weighted blend is made between this estimated elevation profile and the bathymetry data.
- As a result, the land data is unchanged during this process, preserving the accuracy of the coastline.